CN113534727B - Early warning control system of refrigeration equipment for fishing boat based on artificial intelligence platform - Google Patents
Early warning control system of refrigeration equipment for fishing boat based on artificial intelligence platform Download PDFInfo
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Abstract
The invention relates to the technical field of early warning control of fishing boat equipment, in particular to an early warning control system of refrigerating equipment for a fishing boat based on an artificial intelligence platform, which comprises an intelligent adjusting unit, a cloud server, a processing unit, a monitoring unit, a fishing analysis processing unit, a preset unit and an alarm processing unit; the cloud server is used for storing fishing information related to the use record data of the refrigeration equipment on the fishing boat; the intelligent adjusting unit is used for acquiring fishing information from the cloud server and adjusting and identifying the fishing information to the processing unit; the processing unit is used for carrying out data processing on fishing information, and the influence data during the operation of the refrigeration equipment is divided by carrying out identification processing on the related record database in the platform and is subjected to correlation processing, so that the influence data of various types of data is analyzed, the influence data is subjected to unified classification processing, the extraction and search time when the system is used is saved, and the processing speed is accelerated.
Description
Technical Field
The invention relates to the technical field of early warning control of fishing boat equipment, in particular to an early warning control system of refrigerating equipment for a fishing boat based on an artificial intelligence platform.
Background
Refrigeration equipment is mainly used for refrigerating crew food, refrigerating various cargos and conditioning cabin air in summer days, and compression refrigeration equipment is most commonly applied to ships at present, and is used for removing heat of objects and the surroundings thereof through the working cycle of the equipment to cause and maintain a certain low-temperature state.
The refrigeration equipment used on the ship is not on the land and is very troublesome to maintain, so the refrigeration equipment used on a common ship needs to be detected at an indefinite time, and the equipment damage is avoided.
Disclosure of Invention
The invention aims to provide an early warning control system of refrigeration equipment for a fishing boat based on an artificial intelligence platform, which extracts image data of various data by monitoring the real-time data of the refrigeration equipment, performs sum processing calculation on the various data to calculate a calculated value, and performs comparison analysis on the calculated value and a related value detected in real time to determine the normal operation of the refrigeration equipment, increase the data relevance, increase the accuracy of data analysis, increase the reliability of data, save the time consumed by data and improve the working efficiency.
The purpose of the invention can be realized by the following technical scheme: the early warning control system of the refrigeration equipment for the fishing boat based on the artificial intelligence platform comprises an intelligent adjusting unit, a cloud server, a processing unit, a monitoring unit, a fishing analysis processing unit, a setting and judging unit and an alarm processing unit;
the cloud server is used for storing fishing information related to the use record data of the refrigeration equipment on the fishing boat;
the intelligent adjusting unit is used for acquiring fishing information from the cloud server and adjusting and identifying the fishing information to the processing unit;
the processing unit is used for carrying out data processing on the fishing information to obtain a fishing temperature factor, a fishing wind factor, a temperature factor, a ring factor, a fishing season factor, a fishing gas factor, a life mean value, a fishing consumption mean value, an increase value ui, an identification value, an increase factor and a noise safety value through processing, and transmitting the values to the judging unit;
the monitoring unit is used for monitoring real-time system information of the use condition of the refrigeration equipment on the fishing boat in real time and transmitting the real-time system information to the judging unit;
the device comprises a setting and judging unit, a control unit and a control unit, wherein the setting and judging unit is used for processing real information, fishing setting data, a fishing temperature factor, a fishing wind factor, a setting temperature factor, a setting ring factor, a fishing season factor, a fishing gas factor, a life mean value, a fishing consumption mean value, an increase value uv, an identification value, an increase factor and a noise safety value, and processing and judging a non-error signal, a damage signal and a noise modulation signal;
the alarm processing unit is used for identifying and converting the error-free signal, the damaged signal and the noise signal, converting the noise signal into a noise alarm, converting the damaged signal into a damaged alarm, sending the alarm and displaying the alarm.
Further, the specific process of calling and identifying is as follows:
dividing fishing information into fishing data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, temperature data, ring data, fishing season data, fishing gas data, fishing time data, fishing exchange data and fishing record data;
the real system information comprises real data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real memory data.
Further, the specific process of carrying out data processing on the fishing information comprises the following steps:
the fishing analysis unit extracts fishing information from the processing unit, acquires a plurality of same fishing data, extracts corresponding fishing data and fishing replacement data according to the plurality of same fishing data, calculates the difference between the fishing data and the fishing replacement data, calibrates the difference to a service life value, calculates the mean value of the service life values corresponding to the plurality of same fishing data, and calculates the mean value of the service life;
extracting a plurality of fishing data with the same fishing record data, extracting and detecting corresponding fishing consumption data according to the fishing data with the same fishing record data, averaging the fishing consumption data, and calibrating the average fishing consumption data to be a fishing consumption average value;
respectively marking the fishing record data as different use times, extracting fishing consumption mean values corresponding to every two adjacent different times, and performing signal processing on the two corresponding data to obtain an average increasing signal, an increasing signal and a decreasing signal;
judging the signal processing process to obtain an increase value uv and an identification value;
data extraction corresponding fishing noise data are established according to a plurality of fishing, carry out the mean value calculation with a plurality of fishing noise data, calculate fishing noise mean value, carry out the difference value calculation with a plurality of fishing noise data and fishing noise mean value to calculate a plurality of difference value of making an uproar, carry out the mean value calculation with a plurality of difference value of making an uproar, calculate the difference mean value of making an uproar, set for default a1, substitute the formula of calculating with the difference mean value of making an uproar: the noise safety value = the noise difference mean value +/-a 1, and the noise safety value is calculated;
according to the fishing temperature data, the fishing wind data, the temperature data, the ring setting data, the fishing season data, the fishing gas data and the fishing time data corresponding to the fishing data, and the fishing average value, the influence processing is carried out to obtain the fishing temperature factor, the fishing wind factor, the temperature factor, the ring setting factor, the fishing season factor, the fishing gas factor, the fishing time factor and the growth factor.
Further, the specific process of signal processing is as follows:
performing difference value calculation on the fishing consumption mean values corresponding to different time, calculating to obtain a plurality of fishing consumption mean differences, sequencing the fishing consumption mean differences according to fishing record data to obtain fishing consumption mean differences, marking the fishing record data corresponding to each fishing consumption mean difference as an X-axis numerical value, marking the fishing consumption mean difference corresponding to each fishing record data as a Y-axis numerical value, and performing image conversion on each corresponding fishing consumption mean difference and fishing record data to obtain a planar broken line graph, and specifically, performing identification and judgment on the broken line graph:
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are the same, calibrating the fishing record data as average increase consumption, and generating an average increase signal;
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are different and the fishing consumption average difference of the next fishing is larger than the fishing consumption average difference of the previous fishing, calibrating the fishing consumption average difference as ascending and increasing consumption and generating ascending and increasing signals;
and when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are different and the fishing consumption average difference of the next fishing is smaller than the fishing consumption average difference of the previous fishing, calibrating the fishing consumption average difference as the descending and increasing consumption and generating a descending and increasing signal.
Further, the specific process of judging the signal processing process is as follows:
carrying out added value calculation according to the identification and judgment of the broken line graph, sequentially giving identification values 1,2 and 3 to an average increasing signal, an increasing signal and a decreasing signal, and extracting corresponding data according to the average increasing signal, the increasing signal and the decreasing signal;
the consumption value and the identification value are brought into a calculation formula: the consumption value of the second time period = the consumption value (1 + ui) of the first time period, an increase value uv is calculated, v =1,2,3, wherein the consumption value of the second time period refers to the average fish consumption difference corresponding to the next fish record data, the consumption value of the first time period is represented as the average fish consumption difference corresponding to the previous fish record data, and the average increase signal, the increase signal and the decrease signal are sequentially and correspondingly assigned to the identification values 1,2 and 3 to be calibrated as the identification values;
the specific treatment process of the influence treatment comprises the following steps:
respectively comparing fish temperature data, fish wind data, set temperature data, set ring data, fish season data, fish gas data, fish time data and fish consumption data corresponding to the fish setting data through a variable processing method;
respectively keeping one of fishing temperature data, fishing wind data, temperature setting data, ring setting data, fishing season data, fishing gas data and fishing time data as a variable, extracting corresponding fishing consumption data, analyzing influence factors of the corresponding variables on the fishing consumption data according to the variation difference values of a plurality of different variables and the difference values of a plurality of corresponding fishing consumption data, and respectively marking the correspondingly calculated influence factors as a fishing temperature factor, a fishing wind factor, a temperature setting factor, a ring setting factor, a fishing season factor, a fishing gas factor and a fishing time factor;
according to the calculation method of the fish qi factor, the increase value ui corresponding to the fish setting data and the influence calculation of the fish noise data are selected, the increase value influence factor is calculated, and the increase value influence factor is calibrated to be the increase factor.
Further, the specific operation process of the preset sub-judgment operation is as follows:
correspondingly extracting a fish consumption average value, a life average value, fish setting data, a fish temperature factor, a fish wind factor, a temperature factor, a ring setting factor, a fish season factor, a fish gas factor, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data and real time data according to the real setting data, the fish setting data and the real record data, and substituting the fish consumption average value, the life average value, the fish setting data, the fish temperature factor, the real wind data, the real degree data, the real ring data, the real season data, the real gas data and the real time data into a consumption value calculation formula to calculate a calculation consumption value JHi, and carrying out first judgment on the calculation formula to obtain a positive signal and an abnormal signal;
matching the real setting data with the fishing setting data according to the data, selecting corresponding increase values uv, identification values, noise safety values, increase factors, life average values and calculation consumption values, identifying the identification values corresponding to the fishing setting data, selecting the corresponding increase values according to the identification values, bringing the determined increase values uv, the noise safety values, the calculation consumption values, the life average values and the increase factors into a noise value calculation formula, and calculating JZi to represent as a calculation noise value;
extracting and calculating a noise value, and comparing the noise value with real noise data M2, wherein the specific steps are as follows:
when JZi + a1 is larger than M2 is larger than JZi-a1, the noise is judged to be safe, and an ampere signal is generated;
when M2 is not more than JZi-a1 or M2 is not less than JZi + a1, judging that the noise causes auditory influence and generating a danger signal;
the method comprises the following steps of extracting a positive signal, an abnormal signal, an ampere signal and a dangerous signal, and detecting and judging according to the signals, wherein the method specifically comprises the following steps:
when the positive signal and the safety signal are identified at the same time, judging that the refrigeration equipment is normal, and generating an error-free signal;
when the different signal is distinguished or the different signal and the dangerous signal are distinguished at the same time, judging that the refrigeration equipment is damaged, and generating a damage signal;
when the positive signal and the dangerous signal are identified at the same time, the potential safety hazard of the noise of the refrigeration equipment is judged, and a noise modulation signal is generated.
Further, the consumption value calculation formula and the first determination specifically include:
wherein JHi is expressed as a calculated consumption value, SWi is expressed as real temperature data, u1 is expressed as a fish temperature factor, SFi is expressed as real wind data, u2 is expressed as a fish wind factor, SDi is expressed as real degree data, u3 is expressed as a set temperature factor, SHi is expressed as real ring data, u4 is expressed as a set ring factor, SJi is expressed as real season data, u5 is expressed as a fish season factor, SQi is expressed as real gas data, u6 is expressed as a fish gas factor, SSi is expressed as real time data, SMi is expressed as a life mean value, u6 is expressed as an influence factor of the life mean value of the life, e is expressed as a deviation adjustment factor of the calculated consumption value, g is expressed as a conversion adjustment factor of the fish consumption mean value, i =1,2,3 … … n, and n is a positive integer;
extracting and calculating a lower consumption value, and comparing the lower consumption value with the actual consumption data, wherein the specific steps are as follows:
when M1-JHi is less than A1, the consumption value is judged to be normal, and a positive signal is generated;
and when the M1-JHi is more than or equal to A1, judging that the consumption value is abnormal, and generating an abnormal signal, wherein M1 represents actual consumption data, and A1 represents a consumption difference preset value.
The invention has the beneficial effects that:
(1) the influence data of various data are analyzed and uniformly classified by identifying and processing the related recording database in the platform, so that the extraction and search time when the data are used is saved, and the processing speed is accelerated;
(2) the method comprises the steps of monitoring real-time data of the refrigeration equipment, extracting image data of various data, performing sum processing calculation on the various data to calculate a calculated value, comparing and analyzing the calculated value and a related value detected in real time to determine normal operation of the refrigeration equipment, increasing data relevance, increasing accuracy of data analysis, increasing reliability of the data, saving time consumed by the data and improving working efficiency.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to an early warning control system of a refrigeration device for a fishing boat based on an artificial intelligence platform, which comprises an intelligent regulation unit, a cloud server, a processing unit, a monitoring unit, a fish analysis unit, a judgment unit and an alarm unit, wherein the name in the early warning control system is only used for distinguishing different units and types of data, and does not show the functions of the units;
the cloud server is used for storing relevant information of the use record data of the refrigeration equipment on the fishing boat and calibrating the relevant information of the use record data of the refrigeration equipment on the fishing boat as fishing setting information;
the intelligent adjustment unit is used for acquiring fishing information from the cloud server and carrying out adjustment, identification and processing on the fishing information, and specifically comprises the following steps: identifying fishing information as fishing setting data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, temperature setting data, ring setting data, fishing season data, fishing gas data, fishing time data, fishing use data, fishing change data and fishing record data, wherein the fishing setting data refers to refrigeration equipment corresponding to a fishing boat, the fishing consumption data refers to power consumption of the refrigeration equipment on the fishing boat and power consumption rate calculated by division in unit time, the fishing noise data refers to noise of the refrigeration equipment on the fishing boat, the fishing temperature data refers to temperature of the refrigeration equipment on the fishing boat, the fishing wind data refers to blowing size of the refrigeration equipment on the fishing boat, the temperature setting data refers to temperature size of the refrigeration equipment on the fishing boat, the ring data refers to environment temperature size corresponding to the refrigeration equipment on the fishing boat during refrigeration, and the season data refers to season corresponding to the refrigeration equipment on the fishing boat during working, and the seasons are four seasons, namely spring, summer, autumn and winter, the fishing gas data refers to the weather corresponding to the refrigeration equipment on the fishing boat when in work, the weather comprises cloudy days and sunny days, the fishing time data refers to the time corresponding to the refrigeration equipment on the fishing boat when in work, the fishing data refers to the time for starting using the refrigeration equipment on the fishing boat, the fishing change data refers to the time for changing the refrigeration equipment on the fishing boat, the fishing note data refers to the time for using the refrigeration equipment on the fishing boat, and the fishing setting data, the fishing consumption data, the fishing noise data, the fishing temperature data, the fishing wind data, the setting temperature data, the setting ring data, the fishing season data, the fishing gas data, the fishing time data, the fishing change data and the fishing note data are transmitted to the processing unit;
the processing unit transmits the received fishing setting data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, setting temperature data, setting ring data, fishing season data, fishing gas data, fishing time data, fishing exchange data and fishing record data to the fishing analysis unit;
the fishing analysis unit is used for analyzing and processing fishing data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, fishing temperature data, ring data, fishing season data, fishing gas data, fishing time data, fishing replacement data and fishing record data, and the specific operation process of the analysis and processing operation is as follows:
acquiring a plurality of same fishing data, extracting corresponding fishing data and fishing trade data according to the plurality of same fishing data, calculating difference values of the fishing data and the fishing trade data, calibrating the difference values as life values, summing the life values corresponding to the plurality of same fishing data, calculating life sums, dividing the life sums by the number of the plurality of same fishing data, and calculating life average values;
extracting a plurality of fishing data with the same fishing record data, extracting and detecting corresponding fishing consumption data according to the fishing data with the same fishing record data, summing the plurality of fishing consumption data, calculating the total of the fishing consumption data, dividing the total of the fishing consumption data by the number corresponding to the plurality of fishing consumption data, calculating the average value of the fishing consumption data of different fishing record data, and calibrating the average value as a fishing consumption average value, wherein the fishing consumption average value refers to the consumption in a proxy ideal state, namely a numerical value which cannot be influenced by other collected data;
marking the fishing mark data as different use times respectively, extracting fishing consumption average values corresponding to every two adjacent different use times, calculating difference values of the fishing consumption average values and the fishing consumption average values, sequencing the fishing consumption average values according to the fishing mark data to obtain the fishing consumption average values, marking the fishing mark data corresponding to each fishing consumption average value as an X-axis value, marking the fishing consumption average value corresponding to each fishing mark data as a Y-axis value, wherein the image marking refers to marking one type of data as an X-axis value and marking the other type of data as a Y-axis value, and is a very simple marking, for example, the X-axis is time, the Y-axis is corresponding consumption data, and the X-axis and the Y-axis are corresponding, so that a simple rectangular coordinate system of mark points can be formed, the later broken line graphs connect the mark points in turn, and image conversion is carried out on each corresponding fishing mark average value and fishing consumption data, thereby obtain a plane broken line graph, carry out the discernment judgement to the broken line graph, specifically do:
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are the same, calibrating the fishing record data as average increase consumption, and generating an average increase signal;
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are different and the fishing consumption average difference of the next fishing is larger than the fishing consumption average difference of the previous fishing, calibrating the fishing consumption average difference as ascending and increasing consumption and generating ascending and increasing signals;
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are different and the fishing consumption average difference of the next fishing is smaller than the fishing consumption average difference of the previous fishing, calibrating the fishing consumption average difference as descending and increasing consumption and generating descending and increasing signals;
the difference values of the fishing record data between the corresponding sequences of the adjacent fishing consumption average differences are the same;
and (3) carrying out added value calculation according to the identification and judgment of the broken line graph, sequentially giving identification values 1,2 and 3 to the uniformly increasing signal, the increasing signal and the decreasing signal, extracting corresponding data according to the uniformly increasing signal, the increasing signal and the decreasing signal, and bringing the data into a calculation formula: the consumption value of the second time period = the consumption value (1 + ui) of the first time period, an increase value uv is calculated, v =1,2,3, wherein the consumption value of the second time period refers to the average fish consumption difference corresponding to the next fish record data, the consumption value of the first time period is represented as the average fish consumption difference corresponding to the previous fish record data, and the average increase signal, the increase signal and the decrease signal are sequentially and correspondingly assigned to the identification values 1,2 and 3 to be calibrated as the identification values;
data extraction corresponding fishing noise data are established according to a plurality of fishing, a plurality of fishing noise data are summed and calculated, the total of fishing noise data is divided by the number that the corresponding fishing noise data of a plurality of correspond, the average value of fishing noise data is calculated, demarcate it as fishing noise mean value, carry out the difference calculation with a plurality of fishing noise data and fishing noise mean value, thereby calculate a plurality of difference value of making a noise, sum the calculation with a plurality of difference value of making a noise, calculate the total value of making a noise, divide the number of difference value of making a noise with the total value of making a noise, calculate the mean value of making a noise, set for default a1, substitute the formula of calculating with the mean value of making a noise: the noise safety value = the mean value of the noise differences ± a1, the noise safety value is calculated, and the noise safety value refers to noise in an ideal state;
draw the fishing and establish data, fishing temperature data, fishing wind data, establish temperature data, establish ring data, fishing season data, fishing gas data and fishing time data to establish fishing temperature data, fishing wind data that data will correspond, establish temperature data, establish ring data, fishing season data, fishing gas data and fishing time data and fishing that consume the mean value and carry out the influence processing according to the fishing, and the concrete course of treatment of influence is:
respectively comparing fish temperature data, fish wind data, set temperature data, set ring data, fish season data, fish gas data, fish time data and fish consumption data corresponding to the fish setting data through a variable processing method;
respectively keeping one of fishing temperature data, fishing wind data, temperature setting data, ring setting data, fishing season data, fishing gas data and fishing time data as a variable, extracting corresponding fishing consumption data, analyzing influence factors of the corresponding variables on the fishing consumption data according to the variation difference values of a plurality of different variables and the difference values of a plurality of corresponding fishing consumption data, and respectively marking the correspondingly calculated influence factors as a fishing temperature factor, a fishing wind factor, a temperature setting factor, a ring setting factor, a fishing season factor, a fishing gas factor and a fishing time factor;
according to the calculation method of the fish qi factor, selecting an increase value ui corresponding to the fish setting data and the influence calculation of the fish noise data, calculating an increase value influence factor, and calibrating the increase value influence factor as an increase factor;
transmitting the fishing temperature factor, the fishing wind factor, the setting temperature factor, the setting ring factor, the fishing season factor, the fishing gas factor, the life average value, the fishing consumption average value, the increase value ui, the identification value, the increase factor and the noise safety value to a setting and judging unit;
the monitoring unit is used for monitoring the use condition of the refrigeration equipment on the fishing boat in real time and marking the use condition of the refrigeration equipment on the fishing boat monitored in real time as real information, the real information comprises real data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real mark data, wherein the real data refers to the refrigeration equipment corresponding to the fishing boat which is detected in real time, the real consumption data refers to the power consumption of the refrigeration equipment on the fishing boat which is detected in real time and the power consumption rate calculated by dividing the power consumption by unit time, the real noise data refers to the noise size of the refrigeration equipment on the fishing boat which is detected in real time, the real temperature data refers to the temperature size of the refrigeration equipment on the fishing boat which is detected in real time, the real wind data refers to the size of the refrigeration air blowing size of the refrigeration equipment on the fishing boat which is detected in real time, and the temperature size of the refrigeration equipment on the fishing boat which is detected in real time, real-time data refers to the environment temperature corresponding to refrigeration equipment on the fishing boat during refrigeration, real-time data refers to the seasons corresponding to the refrigeration equipment on the fishing boat during working, the seasons are divided into four seasons of spring, summer, autumn and winter, real-time gas data refers to the weather corresponding to the refrigeration equipment on the fishing boat during working, the weather comprises cloudy days and sunny days, real-time data refers to the time corresponding to the refrigeration equipment on the fishing boat during working, and real-time information including real data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real memory data is transmitted to the judgment unit;
the judgment unit is used for carrying out preset judgment operation on received real system information including real data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real record data and fishing set data, a fishing temperature factor, a fishing wind factor, a temperature factor, a ring factor, a fishing season factor, a fishing gas factor, a life mean value, a fishing consumption mean value, a growth numerical value uv, an identification numerical value, a growth factor and a noise safety value, and the specific operation process of the preset judgment operation is as follows:
selecting real data, matching the real data with fishing data, and selecting corresponding real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real record data, fishing temperature factor, fishing wind factor, setting temperature factor, setting ring factor, fishing season factor, fishing gas factor, life average value, fishing consumption average value, growth value uv, identification value, growth factor and noise safety value;
correspondingly extracting a fish consumption average value, a life average value, fish setting data, a fish temperature factor, a fish wind factor, a temperature factor, a ring setting factor, a fish season factor, a fish gas factor, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data and real time data according to the real setting data and the real memory data and substituting the real setting data, the ring setting factor, the fish season factor, the fish gas factor, the real temperature data, the real wind data, the real degree data, the real ring data, the real season data, the real gas data and the real time data into a calculation formula:
wherein JHi is expressed as a calculated consumption value, SWi is expressed as real temperature data, u1 is expressed as a fish temperature factor, SFi is expressed as real wind data, u2 is expressed as a fish wind factor, SDi is expressed as real degree data, u3 is expressed as a set temperature factor, SHi is expressed as real ring data, u4 is expressed as a set ring factor, SJi is expressed as real season data, u5 is expressed as a fish season factor, SQi is expressed as real gas data, u6 is expressed as a fish gas factor, SSi is expressed as real time data, SMi is expressed as a life mean value, u6 is expressed as an influence factor of the life mean value of the life, e is expressed as a deviation adjustment factor of the calculated consumption value, g is expressed as a conversion adjustment factor of the fish consumption mean value, i =1,2,3 … … n, and n is a positive integer;
extracting and calculating a lower consumption value, and comparing the lower consumption value with the actual consumption data, wherein the specific steps are as follows:
when M1-JHi is less than A1, the consumption value is judged to be normal, and a positive signal is generated;
when M1-JHi is larger than or equal to A1, judging that the consumption value is abnormal, generating an abnormal signal, wherein M1 represents actual consumption data, A1 represents a consumption difference preset value and is used for judging the consumption condition in the calculated value;
according to the fact that the data are matched with the fishing setting data, corresponding increase values uv, identification values, noise safety values, increase factors, life average values and calculation consumption values are selected, the identification values corresponding to the fishing setting data are identified, the corresponding increase values are selected according to the identification values, and the determined increase values uv, the noise safety values, the calculation consumption values, the life average values and the increase factors are brought into a calculation formula:
JZi is expressed as a calculated noise value, ZNi is expressed as a noise safety value, JHi is expressed as a calculated consumption value, p1 is expressed as an influence conversion factor of the calculated consumption value on the calculated noise value, p2 is expressed as an influence factor of a life average value on the calculated noise value, and c is expressed as a conversion regulation factor of the life average value and the calculated consumption value, wherein relevant influence values applied to all calculation formulas in the invention are data-quantized, corresponding values are extracted, and the values are substituted into the calculation formulas to calculate data;
extracting and calculating a noise value, and comparing the noise value with real noise data M2, wherein the specific steps are as follows:
when JZi + a1 is larger than M2 is larger than JZi-a1, the noise is judged to be safe, and an ampere signal is generated;
when M2 is not more than JZi-a1 or M2 is not less than JZi + a1, judging that the noise causes auditory influence and generating a danger signal;
the method comprises the following steps of extracting a positive signal, an abnormal signal, an ampere signal and a dangerous signal, and detecting and judging according to the signals, wherein the method specifically comprises the following steps:
when the positive signal and the safety signal are identified at the same time, judging that the refrigeration equipment is normal, and generating an error-free signal;
when the different signal is distinguished or the different signal and the dangerous signal are distinguished at the same time, judging that the refrigeration equipment is damaged, and generating a damage signal;
when a positive signal and a dangerous signal are identified at the same time, judging that potential safety hazards exist in the noise of the refrigeration equipment, and generating a noise modulation signal;
transmitting the error-free signal, the damaged signal and the noise-modulated signal to an alarm unit;
the alarm unit receives the error-free signal, the damage signal and the noise signal, identifies and converts the error-free signal, the damage signal and the noise signal, does not convert the signal when identifying the error-free signal, automatically converts the signal into a noise alarm and displays the noise alarm when identifying the noise signal, and converts the noise alarm into a damage alarm when identifying the damage signal, and sends the alarm and displays the alarm.
When the invention works, the fishing information is obtained from the cloud server through the intelligent adjustment unit, the fishing information is identified as fishing data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, temperature setting data, ring setting data, fishing season data, fishing gas data, fishing time data, fishing use data, fishing change data and fishing record data, and the fishing information is transmitted to the fishing analysis unit through the processing unit, the fishing analysis unit analyzes and processes the fishing data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, temperature setting data, ring setting data, fishing season data, fishing gas data, fishing time data, fishing use data, fishing change data and fishing record data to obtain fishing temperature factor, fishing wind factor, temperature setting factor, ring setting factor, fishing season factor, life average value, fishing consumption average value, growth factor, ui safety factor and fishing record value, the real-time monitoring unit is used for monitoring the use condition of the refrigeration equipment on the fishing boat in real time, marking the use condition of the refrigeration equipment on the fishing boat monitored in real time as real data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real mark data, and transmitting the real data to the setting and judging unit; the judging unit is arranged to carry out preset judging operation on received real system information including real set data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real record data, as well as fish set data, a fish temperature factor, a fish wind factor, a temperature factor, a ring factor, a fish season factor, a fish gas factor, a life average value, a fish consumption average value, a growth value uv, an identification value, a growth factor and a noise safety value to obtain a no-error signal, a damage signal and a noise regulation signal, and transmit the no-error signal, the damage signal and the noise regulation signal to the alarm unit, the alarm unit receives the no-error signal, the damage signal and the noise regulation signal and carries out identification and conversion on the no-error signal, the damage signal and the noise regulation signal, when the no-error signal is identified, the signal is not converted into the noise regulation alarm automatically, and displaying, converting the damage signal into a damage alarm when the damage signal is identified, and giving an alarm and displaying the alarm.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (6)
1. The early warning control system of the refrigeration equipment for the fishing boat based on the artificial intelligence platform is characterized by comprising an intelligent adjusting unit, a cloud server, a processing unit, a monitoring unit, a fishing analysis processing unit, a setting and judging unit and an alarm processing unit;
the cloud server is used for storing fishing information related to the use record data of the refrigeration equipment on the fishing boat;
the intelligent adjusting unit is used for acquiring fishing information from the cloud server and adjusting and identifying the fishing information to the processing unit;
the processing unit is used for carrying out data processing on the fishing information to obtain a fishing temperature factor, a fishing wind factor, a temperature factor, a ring factor, a fishing season factor, a fishing gas factor, a life mean value, a fishing consumption mean value, an increase value ui, an identification value, an increase factor and a noise safety value through processing, and transmitting the values to the judging unit;
the monitoring unit is used for monitoring real-time system information of the use condition of the refrigeration equipment on the fishing boat in real time and transmitting the real-time system information to the judging unit;
the judgment unit is used for processing real information and fishing design data, a fishing temperature factor, a fishing wind factor, a temperature factor, a ring factor, a fishing season factor, a fishing gas factor, a life mean value, a fishing consumption mean value, an increase value uv, an identification value, an increase factor and a noise safety value, and specifically comprises the following steps:
correspondingly extracting a fish consumption average value, a life average value, fish setting data, a fish temperature factor, a fish wind factor, a temperature factor, a ring setting factor, a fish season factor, a fish gas factor, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data and real time data according to the real setting data, the fish setting data and the real record data, and substituting the fish consumption average value, the life average value, the fish setting data, the fish temperature factor, the real wind data, the real degree data, the real ring data, the real season data, the real gas data and the real time data into a consumption value calculation formula to calculate a calculation consumption value JHi, and carrying out first judgment on the calculation formula to obtain a positive signal and an abnormal signal;
matching the real setting data with the fishing setting data according to the data, selecting corresponding increase values uv, identification values, noise safety values, increase factors, life average values and calculation consumption values, identifying the identification values corresponding to the fishing setting data, selecting the corresponding increase values according to the identification values, bringing the determined increase values uv, the noise safety values, the calculation consumption values, the life average values and the increase factors into a noise value calculation formula, and calculating JZi to represent as a calculation noise value;
extracting and calculating a noise value, and comparing the noise value with real noise data M2, wherein the specific steps are as follows:
when JZi + a1 is larger than M2 is larger than JZi-a1, the noise is judged to be safe, and an ampere signal is generated;
when M2 is not more than JZi-a1 or M2 is not less than JZi + a1, judging that the noise causes auditory influence and generating a danger signal;
the method comprises the following steps of extracting a positive signal, an abnormal signal, an ampere signal and a dangerous signal, and detecting and judging according to the signals, wherein the method specifically comprises the following steps:
when the positive signal and the safety signal are identified at the same time, judging that the refrigeration equipment is normal, and generating an error-free signal;
when the different signal is distinguished or the different signal and the dangerous signal are distinguished at the same time, judging that the refrigeration equipment is damaged, and generating a damage signal;
when a positive signal and a dangerous signal are identified at the same time, judging that potential safety hazards exist in the noise of the refrigeration equipment, and generating a noise modulation signal;
transmitting the error-free signal, the damaged signal and the noise-modulated signal to an alarm unit;
the alarm processing unit is used for identifying and converting the error-free signal, the damaged signal and the noise signal, converting the noise signal into a noise alarm, converting the damaged signal into a damaged alarm, sending the alarm and displaying the alarm.
2. The early warning control system of the refrigeration equipment for the fishing vessel based on the artificial intelligence platform as claimed in claim 1, wherein the specific process of calling and identifying is as follows:
dividing fishing information into fishing data, fishing consumption data, fishing noise data, fishing temperature data, fishing wind data, temperature data, ring data, fishing season data, fishing gas data, fishing time data, fishing exchange data and fishing record data;
the real system information comprises real data, real consumption data, real noise data, real temperature data, real wind data, real degree data, real ring data, real season data, real gas data, real time data and real memory data.
3. The early warning control system of the refrigeration equipment for the fishing boat based on the artificial intelligence platform as claimed in claim 2, wherein the specific process of data processing for the fishing information is as follows:
the fishing analysis unit extracts fishing information from the processing unit, acquires a plurality of same fishing data, extracts corresponding fishing data and fishing replacement data according to the plurality of same fishing data, calculates the difference between the fishing data and the fishing replacement data, calibrates the difference to a service life value, calculates the mean value of the service life values corresponding to the plurality of same fishing data, and calculates the mean value of the service life;
extracting a plurality of fishing data with the same fishing record data, extracting and detecting corresponding fishing consumption data according to the fishing data with the same fishing record data, averaging the fishing consumption data, and calibrating the average fishing consumption data to be a fishing consumption average value;
respectively marking the fishing record data as different use times, extracting fishing consumption mean values corresponding to every two adjacent different times, and performing signal processing on the two corresponding data to obtain an average increasing signal, an increasing signal and a decreasing signal;
judging the signal processing process to obtain an increase value uv and an identification value;
data extraction corresponding fishing noise data are established according to a plurality of fishing, carry out the mean value calculation with a plurality of fishing noise data, calculate fishing noise mean value, carry out the difference value calculation with a plurality of fishing noise data and fishing noise mean value to calculate a plurality of difference value of making an uproar, carry out the mean value calculation with a plurality of difference value of making an uproar, calculate the difference mean value of making an uproar, set for default a1, substitute the formula of calculating with the difference mean value of making an uproar: the noise safety value = the noise difference mean value +/-a 1, and the noise safety value is calculated;
according to the fishing temperature data, the fishing wind data, the temperature data, the ring setting data, the fishing season data, the fishing gas data and the fishing time data corresponding to the fishing data, and the fishing average value, the influence processing is carried out to obtain the fishing temperature factor, the fishing wind factor, the temperature factor, the ring setting factor, the fishing season factor, the fishing gas factor, the fishing time factor and the growth factor.
4. The early warning control system of the refrigeration equipment for the fishing vessel based on the artificial intelligence platform as claimed in claim 3, wherein the specific process of signal processing is as follows:
performing difference value calculation on the fishing consumption mean values corresponding to different time, calculating to obtain a plurality of fishing consumption mean differences, sequencing the fishing consumption mean differences according to fishing record data to obtain fishing consumption mean differences, marking the fishing record data corresponding to each fishing consumption mean difference as an X-axis numerical value, marking the fishing consumption mean difference corresponding to each fishing record data as a Y-axis numerical value, and performing image conversion on each corresponding fishing consumption mean difference and fishing record data to obtain a planar broken line graph, and specifically, performing identification and judgment on the broken line graph:
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are the same, calibrating the fishing record data as average increase consumption, and generating an average increase signal;
when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are different and the fishing consumption average difference of the next fishing is larger than the fishing consumption average difference of the previous fishing, calibrating the fishing consumption average difference as ascending and increasing consumption and generating ascending and increasing signals;
and when the fishing consumption average differences corresponding to all fishing record data in the plane line graph are different and the fishing consumption average difference of the next fishing is smaller than the fishing consumption average difference of the previous fishing, calibrating the fishing consumption average difference as the descending and increasing consumption and generating a descending and increasing signal.
5. The early warning control system of the refrigeration equipment for the fishing boat based on the artificial intelligence platform as claimed in claim 4, wherein the specific process of judging the process of signal processing is as follows:
carrying out added value calculation according to the identification and judgment of the broken line graph, sequentially giving identification values 1,2 and 3 to an average increasing signal, an increasing signal and a decreasing signal, and extracting corresponding data according to the average increasing signal, the increasing signal and the decreasing signal;
the consumption value and the identification value are brought into a calculation formula: the consumption value of the second time period = the consumption value (1 + ui) of the first time period, an increase value uv is calculated, v =1,2,3, wherein the consumption value of the second time period refers to the average fish consumption difference corresponding to the next fish record data, the consumption value of the first time period is represented as the average fish consumption difference corresponding to the previous fish record data, and the average increase signal, the increase signal and the decrease signal are sequentially and correspondingly assigned to the identification values 1,2 and 3 to be calibrated as the identification values;
the specific treatment process of the influence treatment comprises the following steps:
respectively comparing fish temperature data, fish wind data, set temperature data, set ring data, fish season data, fish gas data, fish time data and fish consumption data corresponding to the fish setting data through a variable processing method;
respectively keeping one of fishing temperature data, fishing wind data, temperature setting data, ring setting data, fishing season data, fishing gas data and fishing time data as a variable, extracting corresponding fishing consumption data, analyzing influence factors of the corresponding variables on the fishing consumption data according to the variation difference values of a plurality of different variables and the difference values of a plurality of corresponding fishing consumption data, and respectively marking the correspondingly calculated influence factors as a fishing temperature factor, a fishing wind factor, a temperature setting factor, a ring setting factor, a fishing season factor, a fishing gas factor and a fishing time factor;
according to the calculation method of the fish qi factor, the increase value ui corresponding to the fish setting data and the influence calculation of the fish noise data are selected, the increase value influence factor is calculated, and the increase value influence factor is calibrated to be the increase factor.
6. The early warning control system of the refrigeration equipment for the fishing vessel based on the artificial intelligence platform as claimed in claim 5, wherein the consumption value calculation formula and the first judgment are specifically:
wherein JHi is expressed as a calculated consumption value, SWi is expressed as real temperature data, u1 is expressed as a fish temperature factor, SFi is expressed as real wind data, u2 is expressed as a fish wind factor, SDi is expressed as real degree data, u3 is expressed as a set temperature factor, SHi is expressed as real ring data, u4 is expressed as a set ring factor, SJi is expressed as real season data, u5 is expressed as a fish season factor, SQi is expressed as real gas data, u6 is expressed as a fish gas factor, SSi is expressed as real time data, SMi is expressed as a life mean value, u6 is expressed as an influence factor of the life mean value of the life, e is expressed as a deviation adjustment factor of the calculated consumption value, g is expressed as a conversion adjustment factor of the fish consumption mean value, i =1,2,3 … … n, and n is a positive integer;
extracting and calculating a lower consumption value, and comparing the lower consumption value with the actual consumption data, wherein the specific steps are as follows:
when M1-JHi is less than A1, the consumption value is judged to be normal, and a positive signal is generated;
and when the M1-JHi is more than or equal to A1, judging that the consumption value is abnormal, and generating an abnormal signal, wherein M1 represents actual consumption data, and A1 represents a consumption difference preset value.
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